TY - GEN

T1 - Beyond facts

T2 - 1st International Workshop on Knowledge Graphs for Online Discourse Analysis, KnOD 2021

AU - Todorov, Konstantin

AU - Fafalios, Pavlos

AU - Dietze, Stefan

PY - 2021/6/8

Y1 - 2021/6/8

N2 - Expressing opinions and interacting with others on the Web has led to the production of an abundance of online discourse data, such as claims and viewpoints on controversial topics, their sources and contexts. This data constitutes a valuable source of insights for studies into misinformation spread, bias reinforcement, echo chambers or political agenda setting. While knowledge graphs promise to provide the key to a Web of structured information, they are mainly focused on facts without keeping track of the diversity, connection or temporal evolution of online discourse data. As opposed to facts, claims are inherently more complex. Their interpretation strongly depends on the context and a variety of intentional or unintended meanings, where terminology and conceptual understandings strongly diverge across communities from computational social science, to argumentation mining, fact-checking, or viewpoint/ stance detection. The 1st International Workshop on Knowledge Graphs for Online Discourse Analysis (KnOD 2021) aims at strengthening the relations between these communities, providing a forum for shared works on the modeling, extraction and analysis of discourse on the Web. It addresses the need for a shared understanding and structured knowledge about discourse data in order to enable machine-interpretation, discoverability and reuse, in support of scientific or journalistic studies into the analysis of societal debates on the Web.

AB - Expressing opinions and interacting with others on the Web has led to the production of an abundance of online discourse data, such as claims and viewpoints on controversial topics, their sources and contexts. This data constitutes a valuable source of insights for studies into misinformation spread, bias reinforcement, echo chambers or political agenda setting. While knowledge graphs promise to provide the key to a Web of structured information, they are mainly focused on facts without keeping track of the diversity, connection or temporal evolution of online discourse data. As opposed to facts, claims are inherently more complex. Their interpretation strongly depends on the context and a variety of intentional or unintended meanings, where terminology and conceptual understandings strongly diverge across communities from computational social science, to argumentation mining, fact-checking, or viewpoint/ stance detection. The 1st International Workshop on Knowledge Graphs for Online Discourse Analysis (KnOD 2021) aims at strengthening the relations between these communities, providing a forum for shared works on the modeling, extraction and analysis of discourse on the Web. It addresses the need for a shared understanding and structured knowledge about discourse data in order to enable machine-interpretation, discoverability and reuse, in support of scientific or journalistic studies into the analysis of societal debates on the Web.

KW - Computational Fact-checking

KW - Knowledge Graphs

KW - Mis-/Dis-information Spread

KW - Online Discourse Analysis

KW - Social Web Mining

KW - Stance/Viewpoint Detection

UR - http://www.scopus.com/inward/record.url?scp=85108022446&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:85108022446

T3 - CEUR Workshop Proceedings

BT - Knowledge Graphs for Online Discourse Αnalysis 2021

Y2 - 14 April 2021 through 14 April 2021

ER -